The Moderators have been talking about methods to approximate logarithms given only a little bit of information; namely, log102≈0.301 and log103≈0.477. I'm going to go through a couple methods to provide estimates.
It should be noted that the true value of log107 is 0.845098...
Let's start off on a large scale. Obviously, log106<log107<log108. To find log106 and log108, we use the given information. log106=log102+log103≈0.301+0.477=0.778. Also, log108=3log102≈3×0.301=0.903. So 0.778<log107<0.903. Not a very good estimate. Even if we take the average of these, we get 0.8405, which is only accurate to two decimal places.
Let's be a little more creative in our thinking. The set of numbers {48,49,50} includes numbers whose logarithms can be expressed with our given information and a power of 7. Once again, log1048<log1049log1050⇒ log1048<2log107<log1050. The only difference here is that 50 has a power of 5 in its factorization, but log105 can easily be eliminated by noticing that log1050=log102100=log10100−log102=2−log102.
log1048=4log102+log103≈1.681. Also, log1050=2−log102≈1.699. Dividing by 2, we find that 0.8405<log107<0.8495. This is better. Not to mention, taking the average of these values yields log107≈0.8450, accurate to 4 decimal places.
What method would you use to calculate log107? Please share what you think!
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2400log2400log(23×3×102)log23+log3+log1023log2+log3+2log7≈≈≈≈≈≈2401log2401log744log74log70.8450
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So, that begs the question of
1. How do I make such an amazing observation that 2400≈2401?
2. How do I know what the next approximation should be?
Think about this some, before reading my other comment.
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I don't have a solid answer, but I'm thinking we should find larger pairs of numbers such that their percentage difference is as small as the previous, like: 65≈7777=97(104−1)≈97×104 or 67≈280000=104×22×7, but both methods yields 0.844 as the approximation, so I'm kinda stumped right now.
In the meantime, lemme peruse your other comment. =)
There's a 0.04% error in approximating 2401 as 2400, but works out quite well :) +1
@Calvin Lin and @Daniel Liu were the moderators discussing this in our messageboard.
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Cool!! So you guys have a message board of your own?
The general idea is that if you can bound a<7n<b, then you should also look at how ab compares to 72n. This is akin to the Root approximation - bisection method.
For example, from above, we have 6<7<8, which tells us we should compare 48 with 49, and work with 48<49<82.
Explicitly, we can use the following series of inequalities:
Step 1: 6<7<8. Comparing 6×8 with 72, we have 48<72. Hence, this leads to:
Step 2: 48<72<82=64. Comparing 48×64 with 74, we have 74<3072. Hence, this leads to:
Step 3: 2304=482<74<3072. Comparing 2304×3072 with 78, we have 78<7077888. Hence this leads to:
Step 4: 5308416=23042<78<7077888.
We can continue this process indefinitely to bound log7 as tightly as we want to. At step 1, we have 0.778<log7<0.903, and at step 4 we have 0.840<log7<0.856.
Question: Why did I say that this is "akin to the Root approximation - bisection method"?
(see comments below for the explanation)
Note: As it turns out, we could make the observation that 50 a much better bound. With 48<49<50, and so we should compare 48×50 with 492.
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Because you want to find values a,b such that the inequality is satisfied a<7n<b
Taking log to both sides loga<nlog7<logb
Bisection method implies we must minimize the difference between 2loga+logb and nlog7.
Set both of them to be equal implies we want to compare ab to 72n
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Yes. We are performing the bisection method on loga<nlog7<logb. The midpoint of this interval is 2loga+logb=logab. We then compare this to nlog7, which is in essence comparing ab to 72n.
In this way, we don't have to think about what the next number is, or figure out a fancy combination to bound it tightly. We just have to do the bisection method many many times (or automate it with a program), to get the interval down to as small as we want it to.
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I was under the impression, you can only find up to the number of SF given. But this just blew my mind. It's like saying:
"Hey, my calculator is kinda bad, it only let shows that log2=0.3 and log13=1.1 to one decimal place, can you help me find the value of log11 to a gazillion decimal places?"
Thanks, I learned something new today!!
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For example, even if your calculator can only multiply whole numbers, and you want to approximate 2, you can do much better than 1<2<2. For example, by showing that 14142<2000000<14152, we can conclude that 1.414<2<1.415. We can get 2 to any degree of accuracy (with sufficient patience / computing power).
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543543
Well, any method based on the two given information can only be correct to 3 significant figures (or decimal places), because the information itself is correct to only 3 significant figures.
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Not necessarily. For example, if we know log710 to 3 decimal places, then we can get log7 to 4 decimal places.
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It would not be accurate to 3 decimal places. Log 7^10 would only be accurate to 3 significant figures which is 2 decimal places.
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log7. It is independent of the number of sig figs / decimal places that we started off with.
I've added a way to show how we can get an arbitrarily tight bound for